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When remote sensing monitoring rice blast was taken into account, geographical range was widely involved and rice-growing conditions were existing obvious ...
Abstract. It is difficult to determine the health of rice for simple vegetation index (NDVI) thresholding method which is widely used through remote.
Rice Blast Area Monitoring Based on HJ-CCD Imagery. 171 spectrum (Table 1). NDVI is the most widely used vegetation index in monitoring green vegetation respect ...
Rice Blast Area Monitoring Based on HJ-CCD Imagery. https://doi.org/10.1007/978-3-642-36137-1_21 · Full text. Journal: Computer and Computing Technologies ...
Litao Wang, Jidong Xiong, Yagang Du: Rice Blast Area Monitoring Based on HJ-CCD Imagery. CCTA (2) 2012: 168-176. a service of Schloss Dagstuhl - Leibniz ...
Jul 13, 2023 · ... rice leaf blast in large areas based on MODIS remote sensing images [35]. Mandal et al. developed two hyperspectral indices of RBI (R1148 ...
Jun 12, 2024 · PLS-DA was able to classify rice diseases at a sub-field scale, with an overall accuracy of 75.62% and a Kappa value of 0.47. The approach was ...
Jul 13, 2023 · This paper aims to provide insights into current and future trends in remote sensing for rice crop monitoring.
Feb 23, 2023 · Recent advancements in optical sensor technology may make it possible to detect foliar diseases directly in the field (West et al., 2003).
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This study is based on the natural disease in the field, using a six-rotor drone equipped with a six-channel multi-spectral camera Micro-MCA6 Snap to obtain ...